How to Detect Markets Sentiment Anomalies with the Pulsebit API (Python)
How to Detect Markets Sentiment Anomalies with the Pulsebit API (Python) We recently discovered an intriguing anomaly in our sentiment analysis: a 24h momentum spike of +0.273. This spike caught our attention immediately since it indicates a significant shift in market sentiment. Understanding such anomalies can give us an edge in capturing user behavior and market movements, and we want to share how you can leverage this finding using our API. It's easy to overlook sentiment shifts, especially when your pipeline lacks the ability to handle multilingual origins or entity dominance. Imagine this: your model missed this anomaly by 24 hours. During that time, a leading language like English might have dominated the sentiment landscape, masking critical shifts from multilingual sources. If you’re not accounting for these variations, you're leaving potential insights on the table. 
